Field of the Disclosure
The present disclosure relates to a camera, to a camera system comprising a plurality of cameras and to a radar system for use in a camera.
Description of Related Art
Today's autofocus (AF) systems are mostly passive systems. The passive systems can be divided into two sub-categories, the contrast AF and the phase AF. The contrast AF relies on contrast maximization or edge sharpening of one or multiple objects in the scene. From the contrast or sharpness measurement it cannot be determined whether the focus position is too close or too far. Such a focus strategy is usually slow and requires a closed loop transfer function for the precise adjustment of the lens. The phase AF measures the disparity between two (or more) images of the object, which were captured through different parts of the lens aperture. The object distance is calculated from the disparity value by triangulation. The phase AF is faster than the contrast AF but still needs a few iteration steps for the precise adjustment of the lens. Both passive AF systems require a sufficient brightness of the scene. In that case an assist lamp is used to illuminate dark scenes, but this limits the useable depth range to a few meters only.
There are also active AF systems. One active AF system relies on infrared (IR) illuminations and uses an assist lamp usually interfering people's mood before a snapshot. The scene is illuminated with IR light, which is scattered back from the object. The object distance is measured from the time delay of the back-scattered light. Another active AF system uses simple or conventional ultrasonic signals to measure the distance to the object. Such an ultrasonic system is, however, not working when capturing objects through glass panels. Both active AF systems have a limited depth range of only a few meters and cannot measure the speed of objects.
Further, there are AI (artificial intelligence) servo focus systems on the market, e.g. used in the Sony α99 camera. Such AI servo focus systems generally use algorithms that constantly predict where a subject is about to be based on its speed and acceleration data from the autofocus sensor. AI servo is known also as “continuous focus” (AF-C). In focus tracking, it is used to track a subject as it moves around the frame, or towards and away from the camera. When in use, the lens will constantly maintain its focus on the subject, for which purpose it is commonly used for sports and action photography. The AI servo approach is a higher layer calculation of the speed and movements measurements. The artificial intelligence algorithms require lots of processing power raising the price and battery consumption of the camera system. Additionally, this processing causes delay when recording a snapshot. Furthermore, such processing has to be aware of the history of the scene to follow and predict the movement of the object. Sudden snapshots focusing to the objects with highest velocity are impossible.
Other focusing systems do not measure the distance to the object. They rely on sharpening the edges or optimizing the contrast in the picture content. The user touches the location on the screen that he likes to sharpen. The lens wobbles its dynamic range where an algorithm monitors at which lens position the sharpest image is achieved. Finally this lens position is selected. This method is time consuming and too slow for sports photographing, e.g. for focusing on a tennis racket when hitting the ball.
The “background” description provided herein is for the purpose of generally presenting the context of the disclosure. Work of the presently named inventor(s), to the extent it is described in this background section, as well as aspects of the description which may not otherwise qualify as prior art at the time of filing, are neither expressly or impliedly admitted as prior art against the present disclosure.